Model comparison
Compare Cohere Parse 5 and Google Gemini Layout Parser 1.6 using the same provider-sourced document ai rubric. No mystery score and no invented benchmark ranking.
Facts checked September 4, 2026
Set your usage. Your estimate updates as you type.
Counts pages, not files. A 10-page PDF counts as 10 pages. The estimate uses the document-processing rate available for each model.
Estimates exclude taxes, tools, cache storage/writes, free allowances and custom discounts. Image estimates cover output only, not prompt or reference-image charges. Quality modes differ by model. Unlisted settings are not treated as free.
| Model | Access | Estimated total (USD) |
|---|---|---|
| Cohere Parse 5Cohere | Cohere | $0.015 |
| Google Gemini Layout Parser 1.6Google Cloud | Google Cloud | $0.10 |
Quick take
Cohere's compact document parser for turning enterprise PDFs, presentations, and scans into retrieval-ready Markdown and layout metadata.
Parse returns Markdown rather than arbitrary JSON and does not provide confidence scores, header/footer labels, or font hierarchy. Confirm that output contract before replacing a specialized extractor.
Google Cloud's Gemini-assisted parser for preserving document hierarchy and creating context-rich chunks for enterprise search and RAG.
Version 1.6 is a release candidate and uses a global Gemini endpoint. Google explicitly says it does not satisfy its normal data-residency standard, even when the request enters through a US or EU location.
Compare the published facts
Values use each provider's own published units and limits. A blank means the provider did not publish a directly comparable value in the sources reviewed.
| Document AI | Cohere Parse 5 | Google Gemini Layout Parser 1.6 |
|---|---|---|
| Price per pageA current provider rate and the exact page or annotation unit it covers. | $1.50 / 1K pages | $10 / 1K pages, including initial chunking |
| Accepted documentsThe file and document types the listed endpoint is designed to process. | PDF, PPT, JPEG as Base64 | PDF, HTML, DOCX, PPTX, XLSX, XLSM |
| What you get backMarkdown, tables, chunks, fields, descriptions, or another machine-readable result. | Markdown, HTML tables, lists, key-value pairs, image descriptions | DocumentLayout hierarchy, contextual chunks, table/figure descriptions |
| Layout & confidenceWhether the output preserves boxes, hierarchy, labels, reading order, or confidence information. | Page and visual-element locations; no confidence scores | OCR-grounded headings, tables, figures, lists, headers and footers |
| Language coverageProvider-documented language support without inferring unlisted languages. | 9 stable; additional languages zero-shot | Not enumerated for this version |
| Where it runsDirect API, batch service, private environment, marketplace, or regional cloud route. | Cohere API, Model Vault, Microsoft Foundry, SageMaker | Google Cloud Document AI; global Gemini endpoint |
How to choose
Start with the job you need to complete, then validate cost, access, and policy details on your exact provider route.
Cohere enterprise customers can opt out of training; SaaS prompts and generations are generally deleted after 30 days. Private and third-party deployments do not expose customer inputs or outputs to Cohere.
Provider and API links
Google says Document AI customer documents and predictions are not used to train its models. Online documents are processed in memory without disk persistence; batch inputs have a failsafe retention of up to one day.
Provider and API links
Frequently asked questions
Cohere Parse 5: Cohere's compact document parser for turning enterprise PDFs, presentations, and scans into retrieval-ready Markdown and layout metadata. Google Gemini Layout Parser 1.6: Google Cloud's Gemini-assisted parser for preserving document hierarchy and creating context-rich chunks for enterprise search and RAG.
Consider Cohere Parse 5 when your priority is High-volume RAG document ingestion. Consider Google Gemini Layout Parser 1.6 when your priority is RAG over reports, manuals, and filings. Test both with your own data and provider route before committing.
No. This comparison aligns provider-published facts for the Document AI category. It does not claim a universal winner or combine incompatible third-party benchmark scores.
